Published:
2020-06-02
Proceedings:
Proceedings of the AAAI Conference on Artificial Intelligence, 34
Volume
Issue:
Vol. 34 No. 10: Issue 10: AAAI-20 Student Tracks
Track:
Student Abstract Track
Downloads:
Abstract:
Reverse Engineering has been an extremely important field in software engineering, it helps us to better understand and analyze the internal architecture and interrealtions of executables. Classical Java reverse engineering task includes disassembly and decompilation. Traditional Abstract Syntax Tree (AST) based disassemblers and decompilers are strictly rule defined and thus highly fault intolerant when bytecode obfuscation were introduced for safety concern. In this work, we view decompilation as a statistical machine translation task and propose a decompilation framework which is fully based on self-attention mechanism. Through better adaption to the linguistic uniqueness of bytecode, our model fully outperforms rule-based models and previous works based on recurrence mechanism.
DOI:
10.1609/aaai.v34i10.7203
AAAI
Vol. 34 No. 10: Issue 10: AAAI-20 Student Tracks
ISSN 2374-3468 (Online) ISSN 2159-5399 (Print) ISBN 978-1-57735-835-0 (10 issue set)
Published by AAAI Press, Palo Alto, California USA Copyright © 2020, Association for the Advancement of Artificial Intelligence All Rights Reserved